Hi Andre,
This might do it:
A<-data.frame(c("c", "d", "e"),4.4:6.8,c(1,2,3))
colnames(A) <- c ("Family", "NormalizedCount", "Hits")
B<-data.frame(c("c", "f", "a"),c(3.2,6.4, 4.4), c(1,4,3))
colnames(B) <- c ("Family", "NormalizedCount", "Hits")
C<-data.frame(c("q", "o", "f"),c(7.2,9.4, 41.4), c(10,4,5))
colnames(C) <- c ("Family", "NormalizedCount", "Hits")
keepcols<-c("Family","Hits")
D<-merge(A[,keepcols],B[,keepcols],by="Family",all=TRUE)
D<-merge(D,C[,keepcols],by="Family",all=TRUE)
D[,2:4]<-sapply(D[,-1],function(x) { x[is.na(x)]<-0; x })
names(D)<-c("Family","A","B","C")
Jim
On Fri, Feb 24, 2017 at 9:37 AM, André Luis Neves <andrl...@ualberta.ca> wrote:
> Dear R users,
>
> I have the following dataframes (A, B, and C) stored in a list:
>
> A= data.frame(c("c", "d", "e"),4.4:6.8,c(1,2,3))
> colnames(A) <- c ("Family", "NormalizedCount", "Hits")
> A
>
>
> B= data.frame(c("c", "f", "a"),c(3.2,6.4, 4.4), c(1,4,3))
> colnames(B) <- c ("Family", "NormalizedCount", "Hits")
> B
>
>
> C= data.frame(c("q", "o", "f"),c(7.2,9.4, 41.4), c(10,4,5))
> colnames(C) <- c ("Family", "NormalizedCount", "Hits")
> C
>
> mylist <- list(A=A,B=B,C=C)
> mylist
>
>
> My idea is to merge the three dataframes into another dataframe (let's name
> it: 'D') with a structure in which the rows are the Families and columns
> the "Hits" of each family detected in the dataframes A, B, and C. If a
> given 'Family' does NOT have a 'Hit' in the dataframe we need to assign
> number 0 to it.
>
> The dataframe 'D' would need to be populated as follows:
>
>
> Family A
> B C
> c 1 1 0
> d 2 0 0
> e 3 0 0
> f 0 4 5
> a 0 3 0
> q 0 0 10
> o 0 0 4
>
>
> Thank you very much for your great help,
>
>
>
> --
> Andre
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
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